tf.keras.losses.categorical_crossentropy

Computes the categorical crossentropy loss.

View aliases

Main aliases

tf.keras.metrics.categorical_crossentropy, tf.losses.categorical_crossentropy, tf.metrics.categorical_crossentropy

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.losses.categorical_crossentropy, tf.compat.v1.keras.metrics.categorical_crossentropy

tf.keras.losses.categorical_crossentropy(
    y_true, y_pred, from_logits=False, label_smoothing=0
)

Usage:

y_true = [[0, 1, 0], [0, 0, 1]]
y_pred = [[0.05, 0.95, 0], [0.1, 0.8, 0.1]]
loss = tf.keras.losses.categorical_crossentropy(y_true, y_pred)
assert loss.shape == (2,)
loss.numpy()
array([0.0513, 2.303], dtype=float32)

Args
y_true	Tensor of one-hot true targets.
y_pred	Tensor of predicted targets.
from_logits	Whether y_pred is expected to be a logits tensor. By default, we assume that y_pred encodes a probability distribution.
label_smoothing	Float in [0, 1]. If > 0 then smooth the labels.

Returns
Categorical crossentropy loss value.